高超声速滑翔目标自适应跟踪方法

针对机动模式复杂多变的高超声速滑翔目标跟踪问题,提出了一种机动频率自适应跟踪方法。采用介于常速度和常加速度模型之间的Singer模型来表征目标气动力加速度的变化,从而建立跟踪系统的状态方程。根据地基雷达量测量获得系统的量测方程,鉴于距离和角度信息的量级相差较大将其由球形量测量转换为位置量测量。为了适应高超声速滑翔目标灵活多样的机动模式,基于正交性原理和无迹卡尔曼滤波算法实现了Singer模型中机动频率参数的自适应。利用滤波信息计算得到能够反映状态模型误差大小的调整因子,用于放大Singer模型中的机动频率,进而调整状态方程的过程噪声以降低模型误差。通过对2种典型机动轨迹的跟踪仿真,并与交互式多模型等方法进行比较,结果表明所提方法的跟踪精度高、计算量小,能够较好地适应阶跃机动和连续幅值变化的机动。     

Validation and comparison of coordinated turn aircraft maneuvermodels

A major challenge posed by aircraft tracking problems is the nondeterministic nature of an aircraft flight, due to the difficulty of predicting the pilot's actions. Accurate aircraft maneuver models are however highly desirable, particularly in air defense applications, to achieve accurate tracking and prediction. Through analysis of actual fighter aircraft trajectories and comparison with the Singer maneuver model, particularly in terms of prediction performance, coordinated turn (CT) aircraft maneuver models are presented, compared, and validated. A more general CT model is shown to better model actual trajectories than the classical CT model used in the literature     

Manoeuvring target tracking in clutter using particle filters

A particle filter (PF) is a recursive numerical technique which uses random sampling to approximate the optimal solution to target tracking problems involving nonlinearities and/or non-Gaussianity. A set of particle filtering methods for tracking and manoeuvering target in clutter from angle-only measurements is presented and evaluated. The aim is to compare PFs to a well-established tracking algorithm, the IMM-PDA-EKF (interacting multiple model, probabilistic data association, extended Kalman filter), and to provide an insight into which aspects of PF design are of most importance under given conditions. Monte Carlo simulations show that the use of a resampling scheme which produces particles with distinct values offers significant improvements under almost all conditions. Interestingly, under all conditions considered here,using this resampling scheme with blind particle proposals is shown to be superior, in the sense of providing improved performance for a fixed computational expense, to measurement-directed particle proposals with the same resampling scheme. This occurs even under conditions favourable to the use of measurement-directed proposals. The IMM-PDA-EKF performs poorly compared with the PFs for large clutter densities but is more effective when the measurements are precise.     

Improved tracking of maneuvering targets: The use of turn-ratedistributions for acceleration modeling

Tactically maneuvering targets are difficult to track since acceleration cannot be observed directly and the accelerations are induced by human control or an autonomous guidance system therefore they are not subject to deterministic models. A common tracking system is the two-state Kalman filter with a Singer maneuver model where the second-order statistics of acceleration is the same as a first-order Markov process. The Singer model assumes a uniform probability distribution on the targets acceleration which is independent of the x and y direction. In practice, it is expected that targets have constant forward speed and an acceleration vector normal to the velocity vector, a condition not present in the Singer model. The work of Singer is extended by presenting a maneuver model which assumes constant forward speed and a probability distribution on the targets turn-rate. Details of the model are presented along with sample simulation results     

Quantitative SNR analysis for ISAR imaging using jointtime-frequency analysis-Short time Fourier transform

V.C. Chen recently presented an inverse synthetic aperture radar (ISAR) imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. The main reason is because the frequencies of the radar returns of the maneuvering targets are time varying and a JTFA is a technique that is suitable for such signals, in particular a JTFA may concentrate a wideband signal, such as a chirp, while it spreads noise. We quantitatively study the signal-to-noise ratio (SNR) in the ISAR imaging using one of the typical JTFA techniques, namely the short time Fourier transform (STFT). We show that the SNR increases in the joint time-frequency (TF) domain over the one in the time or the frequency domain alone both theoretically and numerically. This quantitatively shows the advantage of the JTFA technique for the ISAR imaging     

利用Singer模型的无陀螺姿态和角速度估计

 给出了一种利用Singer跟踪模型的扩展卡尔曼滤波器 (ExtendedKalmanFilter) ,用于无陀螺姿态和姿态角速度估计。在滤波器中 ,姿态和姿态误差分别由姿态四元数和误差四元数表示 ,而姿态角加速度由一阶Markov过程描述 ,从而避免采用姿态动力学模型。利用数值仿真计算验证了滤波器的性能。在所有的仿真过程 ,滤波器显示出快速收敛能力。稳态估计误差主要由测量更新频率和精度决定。     

Instantaneous Frequency Estimation Using Adaptive Linear Predictor Weights

A computationally efficient scheme for estimating the digital instantaneous frequencies of narrowband inputs is introduced. The frequency estimates are obtained by searching for minima of the inverse input power spectrum. This spectrum is estimated at each input sample from the weights of an adaptive linear predictor which uses the LMS (least mean square) algorithm to update its weights. The related minima are sought via an iterative search algorithm, referred to as the iterative frequency estimator. This algorithm is computationally more efficient than available methods, and also provides a higher resolution. Simulation results are included; these include tracking of random message sequences in FM signals, and the formant frequency estimation of speech.     

Proportional Tracking with Clipped-input Matched Filters

A proportional boresight-error measurement is described for tracking systems that is applicable to envelope-producing matched filters with hard-limited inputs. The error response is derived as a function of input SNR and the filter output SNR is estimated.     

随机共振锁频环路影响因素

针对随机共振锁频环路影响因素不够明朗的问题,在对随机共振锁频环路仿真验证的基础上,重点对信噪比、采样频率和系统参数对环路性能的影响进行了探究。首先,阐述了随机共振锁频环路基本原理,搭建了随机共振锁频环路模拟仿真平台。其次,通过设定不同的信噪比、采样频率和系统参数条件,观察随机共振锁频环路性能变化。最后,总结归纳出各条件对随机共振锁频环路的影响。仿真结果表明,信噪比越低,随机共振锁频环路对信号跟踪性能越差,且最低能够处理信噪比为Eb/N0=1dB的信号。采样频率在高于信号频率50倍时,提高采样频率虽可提高计算精度,但对环路跟踪性能改善作用不大。系统参数是决定随机共振效应能否发生及影响共振效果的关键因素,其表现为一个可供选择的数值区间。     

A discrete event systems approach to discriminating intermittent from permanent faults

Almost all work on model-based diagnosis （MBD） potentially presumes faults are per- sistent and does not take intermittent faults （IFs） into account. Therefore, it is common for diag- nosis systems to misjudge IFs as permanent faults （PFs）, which are the major cause of the problems of false alarms, cannot duplication and no fault found in aircraft avionics. To address this problem, a new fault model which includes PFs and IFs is presented based on discrete event systems （DESs）. Thereafter, an approach is given to discriminate between PFs and IFs by diagnosing the current fault. In this paper, the regulations of （PFs and IFs） fault evolution through fault and reset events along the traces of system are studied, and then label propagation function is modified to account for PFs and the dynamic behavior of IFs and diagnosability of PFs and IFs are defined. Finally, illustrative examples are presented to demonstrate the proposed approach, and the analysis results show the fault types can be discriminated within bounded delay if the system is diagnosable.     

风洞模型-支撑系统涡激振动测量与分析

以0.55m×0.4m低湍流航空声学风洞某模型及其支撑系统为研究对象,采用基于加速度传感器直接测量支撑系统和热线间接测量模型尾流相结合的方法,测量并分析了风洞模型-支撑系统的涡激振动模态,给出了测量方案和数据处理方法。采用基于加速度传感器的功率谱分析方法,获得了模型-支撑系统的三阶振动频率分别为31.1、120.9和221.4Hz;采用基于加速度传感器的频域滤波和频域积分方法,提高了有效信号的信噪比,获得了模型-支撑系统振动的振型和振动节点位置;采用热线测量模型尾流分离涡脱落频率的方法,获得了模型一阶和二阶振动的尾流涡激频率分别为31.1和124.1Hz,并从测量尾流速度脉动量获得了模型振幅变化和抖振边界信息。实验结果表明,采用热线测量模型尾流从而分析模型振动的方法,有利于小尺度的模型振动测量,而且相对于加速度传感器装于模型表面的直接测量方法而言,对试验模型的绕流流场干扰较小,为测量风洞试验模型的涡激振动模态提供了一种方法。     

Frequency line tracking using HMM-based schemes [passive sonar]

This paper deals with fluctuating line tracking, present on the so-called lofargram (low frequency analysis and recording) encountered in any passive sonar system. Considering such a line as a random walk modeled by a first-order Markov chain, we have recourse to the hidden Markov models (HMMs) arsenal. More precisely, we propose to track a frequency line with Viterbi and forward-backward algorithms. The originality of this work comes from the fact that a "probabilistic integration of the spectral power" approach allows us to construct a signal-to-noise (SNR)-knowledge-free method. Intensive simulations reveal no loss of performance.     

Frequency-Agile Radar Signal Processing

Modern radars may incorporate pulse-to-pulse carrier frequency modulation to increase probability of detection, to reduce Vulnerability to jamming, and to reduce probability of interception. However, if coherent processing is used for clutter rejection, the frequency of N consecutive pulses must be held constant for N-pulse clutter cancellation or Doppler filtering. If M pulses are transmitted during the time the antenna illuminates a target, there are M/N coherently integrated echoes available for noncoherent integration in the computer or the operator's display to further improve the signal-to-noise ratio (SNR). In this paper, analytical and simulation methods are employed to determine the balance between coherent and noncoherent integration that yields the greatest SNR improvement. Attention is focused upon a model using peak selection of fast Fourier transform (FFT) Doppler channels and is compared to a reference model involving only a single Doppler channel. Curves of detectable SNR as a function of M and N are presented for both models.     

Likelihood-ratio detection of frequency-hopped signals

The optimum system for intercepting frequency-hopped signals uses a channelized receiver and a likelihood-ratio test (LRT). Previous results on the performance of the optimum system have been based on Gaussian assumptions, which are generally valid for transmissions having large time-bandwidth areas. Results, obtained by Monte Carlo simulation, for relatively small time-bandwidth transmissions are given here. The signal model is a simple one known as “pure frequency hopping.” Comparisons with the LRT show that energy detection loss increases when the time-bandwidth product of the transmission is increased by increasing the number of frequencies, even when the number of pulses is also increased. The loss decreases when only the number of pulses is increased. Over the parameter range observed, binary detection loss tends to increase with the number of pulses and decrease with the number of frequencies. Results are included for a moving-window version of the LRT. A parameter of the LRT is the signal-to-noise ratio (SNR). The effect of using a design value not equal to the true SNR is shown     

一种基于径向加速度的Singer-EKF机动目标跟踪算法

针对雷达均不能提供目标加速度信息,在目标机动时会出现跟踪精度差甚至跟踪发散的问题,提出一种基于径向加速度的Singer-EKF算法。该算法在信号处理阶段利用Radon-Ambiguity变换（RAT）估计出目标的径向加速度,并通过坐标转换将其引入量测向量中,然后采用基于Singer模型的扩展卡尔曼滤波（EKF）算法实现机动目标的跟踪。仿真验证了该方法的有效性,并与传统的不带径向加速度的扩展卡尔曼滤波（EKF）方法进行了比较,结果表明该方法在径向距离、位置、加速度和速度估计精度方面都有所提高。     

一种高动态低信噪比下载波快速捕获跟踪方法

针对高动态、低信噪比的接收信号,首先对整个多普勒频率范围进行分段,并在每一段内利用本地产生的带有多普勒频率变化率的复信号来抵消接收信号中多普勒频率变化率的影响,然后在每一段内利用FFT（FastFourierTransform,快速傅里叶变换）进行载波频率并行捕获,从而同时完成载波多普勒频率及其变化率的初步估计。利用载波多普勒频率及其变化率估计信息辅助锁频环快速入锁,进而利用锁频环辅助三阶锁相环完成载波信号的锁频锁相跟踪。使用这种方法,可以快速获取信号的多普勒频率及其变化率信息,并且在极短时间内完成载波的稳定跟踪,使接收设备具备快速捕获跟踪大动态弱信号的能力。     

Directed Subspace Search ML-PDA with Application to Active Sonar Tracking

The maximum likelihood probabilistic data association (ML-PDA) tracking algorithm is effective in tracking Very Low Observable targets (i.e., very low signal-to-noise ratio (SNR) targets in a high false alarm environment). However, the computational complexity associated with obtaining the track estimate in many cases has precluded its use in real-time scenarios. Previous ML-PDA implementations used a multi-pass grid (MPG) search to find the track estimate. Two alternate methods for finding the track estimate are presented-a genetic search and a newly developed directed subspace (DSS) search algorithm. Each algorithm is tested using active sonar scenarios in which an autonomous underwater vehicle searches for and tracks a target. Within each scenario, the problem parameters are varied to illustrate the relative performance of each search technique. Both the DSS search and the genetic algorithm are shown to be an order of magnitude more computationally efficient than the MPG search, making possible real-time implementation. In addition, the DSS search is shown to be the most effective technique at tracking a target at the lowest SNR levels-reliable tracking down to 5 dB (postprocessing SNR in a resolution cell) using a 5-frame sliding window is demonstrated, this being 6 dB better than the MPG search.     

Modeling and Estimation for Tracking Maneuvering Targets

A new approach to the three-dimensional airborne maneuvering target tracking problem is presented. The method, which combines the correlated acceleration target model of Singer [3] with the adaptive semi-Markov maneuver model of Gholson and Moose [8], leads to a practical real-time tracking algorithm that can be easily implemented on a modern fire-control computer. Preliminary testing with actual radar measurements indicates both improved tracking accuracy and increased filter stability in response to rapid target accelerations in elevation, bearing, and range.     

基于增量学习的非定常气动力参数化降阶模型

气动降阶模型（ROM）是预测非定常气动力的有效工具,具有高精度和低计算成本的优点,近年来许多研究证实了该方法的有效性。但是关于飞行参数变化时,ROM的鲁棒性还需要进一步提高。为了提高ROM对不同飞行参数下的气动力预测能力,提出了基于最小二乘支持向量回归（LS-SVR）和增量学习算法的参数化降阶模型。LS-SVR是一种具有良好泛化能力的回归方法,基于LS-SVR的增量学习算法的主要贡献是在增加新样本集时,不需要重新学习整个数据集。为说明该方法的有效性,基于两自由度NACA64A010翼型构建参数化非定常气动力降阶模型。为了训练气动力输入和相应输出之间的关系,将马赫数和迎角作为附加的模型输入。仿真结果表明,该降阶模型能够准确描述气动力和气动弹性系统在不同飞行参数下的动态特性。     

Design and Application of an Adaptive Tracking Filter Control System

The design of an adaptive tracking filter control system and its application to large flexible booster vehicles is described. The problem of elastic vehicle stability is considered along with its solution by conventional and adaptive techniques. The improvement in vehicle stability, which may be achieved with the adaptive tracking filter technique as compared to conventional techniques, is shown. The control system evolved uses two adaptive tracking filters to phase stabilize the first and second bending modes, in addition to conventional compensation techniques. The application of this adaptive technique to a vehicle in which the modal frequencies are in close proximity (<2.5 percent separation) is discussed. The mechanization of the adaptive control system involves the selection of design techniques and components that are electrically and physically compatible with the intended airborne application. The development of a suitable frequency tracking technique and tracking filter is described, in addition to the electronic and mechanical design of the adaptive control system prototype.